Satellite observations of changes in snow-covered land surface albedo during spring in the Northern Hemisphere

• Published in: The Cryosphere
• Main Authors: K. Atlaskina, F. Berninger, G. de Leeuw
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus Publications 2015
• Subjects: Environmental sciences; GE1-350; Geology; QE1-996.5; Chukotka; Chukotka Peninsula; The Cryosphere; Siberia
• Online Access: https://doi.org/10.5194/tc-9-1879-2015; https://doaj.org/article/fae5266c856f48e4aff204ca5ac09e1c

Thirteen years of Moderate Resolution Imaging Spectroradiometer (MODIS) surface albedo data for the Northern Hemisphere during the spring months (March–May) were analyzed to determine temporal and spatial changes over snow-covered land surfaces. Tendencies in land surface albedo change north of 50° N were analyzed using data on snow cover fraction, air temperature, vegetation index and precipitation. To this end, the study domain was divided into six smaller areas, based on their geographical position and climate similarity. Strong differences were observed between these areas. As expected, snow cover fraction (SCF) has a strong influence on the albedo in the study area and can explain 56 % of variation of albedo in March, 76 % in April and 92 % in May. Therefore the effects of other parameters were investigated only for areas with 100 % SCF. The second largest driver for snow-covered land surface albedo changes is the air temperature when it exceeds a value between −15 and −10 °C, depending on the region. At monthly mean air temperatures below this value no albedo changes are observed. The Enhanced Vegetation Index (EVI) and precipitation amount and frequency were independently examined as possible candidates to explain observed changes in albedo for areas with 100 % SCF. Amount and frequency of precipitation were identified to influence the albedo over some areas in Eurasia and North America, but no clear effects were observed in other areas. EVI is positively correlated with albedo in Chukotka Peninsula and negatively in eastern Siberia. For other regions the spatial variability of the correlation fields is too high to reach any conclusions.